Fast, accurate and individualised calculation or estimation of an animal weight is important in many commercial fields. In agriculture, for example, estimation of carcass weight is important in efficient livestock processing operations, such as growth control and pricing. Accurately estimating a livestock animal's weight and/or final carcass weight can result in significant cost savings to the livestock producers, as they are often penalised when any of the animals they produce have a weight or volume outside of the range determined by the slaughter. Also, growth monitoring, feeding optimisation and management of batches is currently done in an uncontrolled manner, and accuracy of the methods relies on producer's criteria.
There exist a number of approaches to accurately weight animals; however, these are based on the use of scales which are logistically impractical and stressful for the animals, which less to an overall reduction of the yield. For instance, the most common approach to estimate the weight of a pig is based on experience after visual evaluation of the producer.
In an experimental evaluation on a sample of 45 pigs it has been found that overall pig weighting based on observation was indeed correlated. For this specific test the inventors of this invention has found that root mean squared error was about 6.4 Kg for pigs ranging from 70 to 140 Kg. This resulted in a Pearson's correlation of 0.90 and R2 coefficient of 0.80. Obviously, this result is a reference and variability in error might depend in many factors that might increase or reduce overall accuracy. This leads to the conclusion that observation has an important degree of uncertainty, which is a disadvantage for business.
Optiscan currently commercialized by Ro-main (disclosed in US-20100222684) is based on three dimensional (3D) imaging of the pig and subsequent processing of data to estimate the overall pig weight.
Other known technologies to estimate body conditions of animals are disclosed in WO-A1-2010/063527 providing an arrangement that comprises a three-dimensional camera system directed towards the animal and provided for recording at least one three-dimensional image of the animal, and an image processing device connected to the three-dimensional camera system and provided for forming a three-dimensional surface representation of a portion of the animal from the three-dimensional image recorded by the three-dimensional camera system; for statistically analyzing the surface of the three-dimensional surface representation; and for determining the body condition score of the animal based on the statistically analyzed surface of the three-dimensional surface representation.
Also WO-A2-2010/098954 discloses methods, systems, and apparatus for estimating physical parameters using three dimensional representations. In this case, predetermined light patterns are projected onto an object and light patterns resulting from an interaction of the projected light patterns and portions of the object are detected. Three dimensional locations of multiple light elements in the detected light pattern are determined, and physical parameters of the object, for example, weight, are estimated based on the locations.
Similarly, WO-A1-2004/012146 presents an imaging method and system for use in automatic monitoring the body condition of an animal. A predetermined region of interest on the animal body is imaged, and data indicative of the acquired one or more images is processed to obtain a three-dimensional representation of the region of interest. The three-dimensional representation is analyzed to determine a predetermined measurable parameter indicative of a surface relief of the region of interest which is indicative of the body condition of the imaged animal.
US-A1-2005257748 discloses a method and apparatus for measuring the physical characteristics of livestock animals such as cattle and hogs. The apparatus of this patent application includes a plurality of strategically positioned cameras that are used to obtain data concerning volumetric, curvilinear (surface) and linear measurements of the livestock animals and the full carcasses thereof. The data is then analysed to provide information that substantially assists the commercial producer of livestock animals in producing a high-quality end-product for the consumer while adding profitability to the enterprise.
Finally, US-A1-2008/0140234 discloses a method for remotely directing a fishing tournament making use of a data network over which participants transmit submissions indicating sizes of fish caught. In this case, this patent application allows performing the submissions by including digital images of fish. Moreover, the size of the fish may be determined from a scale established using a reference object depicted in the image.
Apart from that, Visual image analysis (VIA) uses aerial-view images of animals to determine body surface dimensions and may be used for real-time monitoring of pig growth [1]. FIG. 2 shows an example of body parts used to compute the pig weight. A UK company is currently commercializing the implementation of this work to monitor pig growth. Recently, a PhD Thesis [2] evaluated the ability of Qscan to accurately estimate: (1) live body weight (BW) of individual pigs, and (2) mean BW for groups of pigs. Conclusions of this work were to not recommend Qscan for predicting BW of individual pigs.
The present invention provides further improvements in the field.